-
Je něco špatně v tomto záznamu ?
Modeling pre-spawning fitness and optimal climate of spotted snakehead Channa punctata (Bloch, 1793) from a Gangetic floodplain wetland of West Bengal, India
G. Karnatak, UK. Sarkar, M. Naskar, K. Roy, S. Nandi, P. Mishal, L. Lianthuamluaia, S. Kumari, BK. Das,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
Grantová podpora
NICRA 2017-20
Indian Council of Agricultural Research (IN)
NLK
ProQuest Central
od 2003-03-01 do Před 1 rokem
Medline Complete (EBSCOhost)
od 2011-01-01 do Před 1 rokem
Health & Medicine (ProQuest)
od 2003-03-01 do Před 1 rokem
- MeSH
- ekosystém * MeSH
- klimatické změny MeSH
- mokřady * MeSH
- řeky MeSH
- rozmnožování MeSH
- zvířata MeSH
- Check Tag
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Indie MeSH
The spawning and well-being of fish in an ecosystem are closely linked to climatic cues, viz., temperature and rainfall. Reduced fitness can affect the reproductive performance and lead to skipped spawning. Benchmarking the threshold fitness required for a fish population to achieve readiness for spawning, and understanding how climatic parameters influence the fitness will aid in predicting the fate of its reproductive success in future climatic conditions. This study determined the threshold condition factor pre-spawning fitness (Kspawn50) at which 50% of the female Channa punctata population can be deemed fit for spawning. The optimal climate within which pre-spawning fitness is attained by this species under Indian climatic conditions was also identified. The study was conducted from June 2015 to September 2016, covering two spawning seasons (June-August) in a Gangetic floodplain wetland of West Bengal, India. The non-parametric Kaplan-Meier method (survival fit) was used for estimation of pre-spawning fitness. "Ready to spawn" females were classified based on binary coding of the gonadal maturity stages. The thermal and precipitation range within which spawning fitness is achieved was identified by using the locally weighted smoothing technique. Female C. punctata pre-spawning fitness (Kspawn50) ranged from 1.26 to 1.39 with an estimated median of 1.29 units. Temperatures between 29 and 32 °C and rainfall above 100 mm were conducive to attaining the requisite pre-spawning fitness in C. punctata. This is the first study benchmarking the pre-spawning fitness and optimal climate for C. punctata. Understanding spawning requirements can inform the climate change-induced impacts on reproductive plasticity and evolutionary adaptations of snakeheads in the Ganga river basin.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc20027682
- 003
- CZ-PrNML
- 005
- 20210114152225.0
- 007
- ta
- 008
- 210105s2020 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1007/s00484-020-01976-z $2 doi
- 035 __
- $a (PubMed)32897434
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Karnatak, Gunjan $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 245 10
- $a Modeling pre-spawning fitness and optimal climate of spotted snakehead Channa punctata (Bloch, 1793) from a Gangetic floodplain wetland of West Bengal, India / $c G. Karnatak, UK. Sarkar, M. Naskar, K. Roy, S. Nandi, P. Mishal, L. Lianthuamluaia, S. Kumari, BK. Das,
- 520 9_
- $a The spawning and well-being of fish in an ecosystem are closely linked to climatic cues, viz., temperature and rainfall. Reduced fitness can affect the reproductive performance and lead to skipped spawning. Benchmarking the threshold fitness required for a fish population to achieve readiness for spawning, and understanding how climatic parameters influence the fitness will aid in predicting the fate of its reproductive success in future climatic conditions. This study determined the threshold condition factor pre-spawning fitness (Kspawn50) at which 50% of the female Channa punctata population can be deemed fit for spawning. The optimal climate within which pre-spawning fitness is attained by this species under Indian climatic conditions was also identified. The study was conducted from June 2015 to September 2016, covering two spawning seasons (June-August) in a Gangetic floodplain wetland of West Bengal, India. The non-parametric Kaplan-Meier method (survival fit) was used for estimation of pre-spawning fitness. "Ready to spawn" females were classified based on binary coding of the gonadal maturity stages. The thermal and precipitation range within which spawning fitness is achieved was identified by using the locally weighted smoothing technique. Female C. punctata pre-spawning fitness (Kspawn50) ranged from 1.26 to 1.39 with an estimated median of 1.29 units. Temperatures between 29 and 32 °C and rainfall above 100 mm were conducive to attaining the requisite pre-spawning fitness in C. punctata. This is the first study benchmarking the pre-spawning fitness and optimal climate for C. punctata. Understanding spawning requirements can inform the climate change-induced impacts on reproductive plasticity and evolutionary adaptations of snakeheads in the Ganga river basin.
- 650 _2
- $a zvířata $7 D000818
- 650 _2
- $a klimatické změny $7 D057231
- 650 12
- $a ekosystém $7 D017753
- 650 _2
- $a ženské pohlaví $7 D005260
- 650 _2
- $a rozmnožování $7 D012098
- 650 _2
- $a řeky $7 D045483
- 650 12
- $a mokřady $7 D053833
- 651 _2
- $a Indie $7 D007194
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Sarkar, Uttam Kumar $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India. uksarkar1@gmail.com.
- 700 1_
- $a Naskar, Malay $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 700 1_
- $a Roy, Koushik $u Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Institute of Aquaculture and Protection of Waters, University of South Bohemiain České Budějovice, 370 05, České Budějovice, Czech Republic.
- 700 1_
- $a Nandi, Saurav $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 700 1_
- $a Mishal, Puthiyottil $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 700 1_
- $a Lianthuamluaia, Lianthuamluaia $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 700 1_
- $a Kumari, Suman $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 700 1_
- $a Das, Basanta Kumar $u ICAR-Central Inland Fisheries Research Institute, Kolkata, West Bengal, 700120, India.
- 773 0_
- $w MED00002297 $t International journal of biometeorology $x 1432-1254 $g Roč. 64, č. 11 (2020), s. 1889-1898
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/32897434 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20210105 $b ABA008
- 991 __
- $a 20210114152224 $b ABA008
- 999 __
- $a ok $b bmc $g 1608017 $s 1118862
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2020 $b 64 $c 11 $d 1889-1898 $e 20200908 $i 1432-1254 $m International journal of biometeorology $n Int J Biometeorol $x MED00002297
- GRA __
- $a NICRA 2017-20 $p Indian Council of Agricultural Research (IN)
- LZP __
- $a Pubmed-20210105